6 Steps to Consider When Starting a Career in Data Science
Working as a data science make you feel happy about it. For you to feel happy in the field you should try and have a clue of what is expected of you. When I say this I don’t mean you need experience for you to succeed in the business. If you are eager to know where you need to start in your data science career then here are the 6 steps to follow.
The first thing is to know what you need. This is the first and very crucial point to start your data science career if you want to be in the right place. The main thing here is to understand where you are at the moment and what you want to achieve. For you to complete with that step you will need to explain the meaning of data science. The process of asking questions and answering them in numeric data is what we call data science. The results of this step are a huge amount of data that can be tiresome if handled by a human being and that’s why it’s good to uses a program. When you use the program you will get the advantage that the program will take all the questions and work on it before releasing results. With a scientist who has the knowledge of writing a program will be of great help to you but you have to make sure you are fluent mathematically. Additionally, you need to be constant on one or more languages when coding.
Python and R are the first the second step to consider. The use of R is to compute statistical data like data manipulation, storage and also graphing. Python simplifies your work that looks a lot when you use other languages. It’s a good idea to start with a single language until you are sure you are good at it. You will need to perfect in semantics, structures ad basics function until you sing them like a song.
Pursuing a degree is the next step for a data scientist. A degree in either information technology, computer science mathematics or statistics will be an advantage to your data science career because you will get into details of your career and you will also be close to experts in the field hence giving you a chance to ask any question that you may have.
Then, you should learn about specialization. Since the data science is an umbrella of many specializations you should find the direction to take depending on your interest.
Practical applications is the way to follow. In your field of concentration its good you be careful with the theory part of it so that you will learn how the program works and how it behaves with certain syntax but you also need the practical part of it for you to be able to use it.
Finally, you will need to have an independent project to ensure you get the details of theory in action.